Comment by Animats | Hacker News Reader

Comment by Animats | Hacker News Reader

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Interesting. Frequency-modulated continuous-wave LIDAR is easy to do as a one-point device. Many such devices have been built. But they're usually short range, such as the discontinued Swiss Ranger, and don't reject ambient light as effectively as pulse systems.

Being both eye-safe and sunlight-tolerant is hard. Eye-safe is easier if you can increase the diameter of the outgoing beam. Eye safety is measured based on beam energy through a 1/4" hole (an eye pupil), and if the outgoing beam is made wider (say an inch) the energy per unit area drops. But the optics become bigger. Flash LIDAR units emit a spreading beam, and if you can keep people from getting close to the emitter and staring into it, it's not a big problem. (It's a distance measuring device, so if it detects something at range < 1 foot, it must cut the power way down.)

Sunlight tolerant is done with a few tricks. Narrow-band interference filters cut out everything but the color of the beam being used. A pulse LIDAR can outshine the sun for a nanosecond. Continuous-wave systems could in theory operate below the noise threshold, but the detector has to not saturate.

Anyway, there are lots of technologies that can work. Continental bought Advanced Scientific Concepts' technology, which is known to work fine; it just cost too much when each unit was built by PhDs in Santa Barbara. Continental is a huge auto parts maker; making a million of something cheaply is what they do.

The Mesa Imaging SwissRanger is an amplitude modulated system, not frequency modulated. It's also not really LIDAR, as it uses LED illumination, but AMCW LIDAR is more or less the same principle. A better comparison might be laser tape measures - these often use phase modulated LIDAR rather than direct ToF. You can also buy phase shift scanning systems from people like Leica Geosystems.

In a ToF camera (at least some of them - see lock-in pixels), each pixel is sampled four times per cycle to detect the phase offset from the outgoing illumination. The SwissRanger was one of the first time of flight cameras. The reason it suffers short range is because of phase ambiguity - the lasers are modulated at around 30MHz which gives a wavelength of 10 m or so. The ambiguity distance is half this (5 m). LIDAR systems historically got round this by using multiple modulation frequencies for different distance scales.

This tech is now everywhere thanks to Microsoft buying Canesta.

Leica Geosystems used to sell phase-based scanners. These units were actually rebadged Zoller+Frohlich scanners. But the partnership ended a few years ago when Leica introduced the Pxx series. Today the company only makes time-of-flight scanners.

source: I work at Leica Geosystems.

You can get some pretty impressive dynamic range out of the new silicon photomultiplier detectors that companies like SensL, Hamamatsu, and Ketek have been putting out.

Despite the name, they aren't related to old-school photomultipliers - they're basically large arrays of very tiny Geiger-mode avalanche photodiodes on a single chip. This solves the low dynamic range issues from traditional large-area avalanche photodiodes. Traditional APDs have a long recovery time, whereas an array of small APDs has both a shorter recovery time per cell as well as a greater overall dynamic range due to the ability of multiple cells to be struck at once by incident photons.

SensL actually has a bunch of videos of their products in use for a LIDAR application: http://sensl.com/applications/lidar1/

Advanced Scientific Concepts built some actual photomultiplier LIDAR devices for DoD. Photomultipliers have very low latency - picoseconds. One photon in, one electron out. So they built an InGaAs sensor as the target of a photomultiplier tube. Sensitivity is very good, but the technology is expensive.

There's a promoted comment on the original post that addresses the question of interference between lidars from multiple cars on the same street (short version: coded pulses so each unit can recognise its own reflections). But your comment makes me wonder about another issue: what about eye safety in a street crowded with autonomous cars? Each car's lidar may be eye safe on its own, but how safe is a busy street that's being continually scanned by dozens of cars at once?

I think more graceful failure modes would be better as well. One thing that AI systems don't seem to do a lot of nowadays is quantify their failure level. Voice assistants always reply with the same degree of sureness leading to some silly situations that wouldn't occur with a human. (Despite them having a confidence score)

It's not that better and better solutions are bad but there are probably a lot more gains in mitigating failure cases. I think our brains may even have dedicated systems for potential failure detection leading to timidness. Failure is currently mostly defined as lack of ability to get the right answer, it is negatively defined. I wonder is there's any merit in positively defining failure.

Another way to think of it is if timidness/shyness, typically "negative" traits (especially in American culture) are actually features rather than bugs.

Another way for a CW lidar to work is to use diffraction optics trick of some kind, some smart coding scheme, and a lot of computing power to do a lot of Fourier transforms.

Continuous ToF calculation from a specially coded continuous signal is already used in Chinese military rangefinders (coded continuous signal is hard to spot unlike repetitive pulses)

> Sunlight tolerant is done with a few tricks. Narrow-band interference filters cut out everything but the color of the beam being used.

What about a beam collimator at the detector? It would reject a lot of noise but would cost some power.

COntinental Bought High flash 3D Lidar company. It seems promising to detect objects at 200mts and at very less cost compared to velodyne Lidars.

Isn't flash lidar range limited unless at a very high power output?

The peak power output is high, but only for a nanosecond or less.

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